Denoising RENOIR Image Dataset with DBSR

Fatma Albluwi, Vladimir A. Krylov, Rozenn Dahyot

Research output: Contribution to conferencePaperpeer-review

Abstract

Noise reduction algorithms have often been evaluated using images degraded by artificially synthesised noise. The RENOIR image dataset [3] provides an alternative way for testing noise reduction algorithms on real noisy images and we propose in this paper to assess our CNN called De-Blurring Super-Resolution (DBSR) [2] to reduce the natural noise due to low light conditions in a RENOIR dataset.
Original languageEnglish
DOIs
Publication statusPublished - 1 Jan 2019
Externally publishedYes
EventIMVIP 2019: Irish Machine Vision & Image Processing - Technological University Dublin, Dublin, Ireland
Duration: 28 Aug 201930 Aug 2019

Conference

ConferenceIMVIP 2019: Irish Machine Vision & Image Processing
Country/TerritoryIreland
CityDublin
Period28/08/1930/08/19

Keywords

  • Noise reduction
  • RENOIR image dataset
  • CNN
  • De-Blurring Super-Resolution
  • natural noise
  • low light conditions

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